light_triad

Best demo - it's Claude Code all the way down. Claude Code === Claude Code

Thanks for this - exciting launch. Do you have examples of cool applications or demos that the HN crowd should check out?

Makes sense given what Nadella recently said:

- Self claiming some AGI milestone is "non-sensical benchmark hacking"

- The AI model race won't be winner-take-all

- The real benchmark is if the world is growing at 10%

MSFT is putting its focus on AI adoption in the app layer and "at-scale consumer properties"

Full conversation: https://www.youtube.com/watch?v=4GLSzuYXh6w

Partly because coding has become so hyper specialised in large companies, partly because folks who sell AI have an incentive to exaggerate to sell more.

Programming is over, jobs will disappear and we'll all be on UBI while AI turns into terminator. Meanwhile designing software systems still requires lots of intrinsic motivation and persistence

Agreed UX can be easily copied, but brands are a moat for a number of (granted, psychological) reasons:

1. Status symbols - my Lambo signifies that my disposable income is greater than your disposable income

2. Fan clubs - I buy Nikes because they do a better job at promoting great athleticism, and an iPhone to pay double for hardware from 3 years ago

3. Visibility bias - As a late adopter I use whatever the category leader is (i.e. ChatGPT = AI, Facebook = the Internet)

What you describe sounds more like market power resulting from a monopoly

AI enables new tools & features but in itself is not a product.

There's a good essay from Andrew Chen on this topic: Revenge of the GPT Wrappers: Defensibility in a world of commoditized AI models

"Network effects are what defended consumer products, in particular, but we will also see moats develop from the same places they came from the past decades: B2B-specific moats (workflow, compliance, security, etc), brand/UX, growth/distribution advantages, proprietary data, etc etc." [1]

Also check out the podcast with the team at Cursor/Anysphere for details into how they integrate models into workflows [2]

[1] https://andrewchen.substack.com/p/revenge-of-the-gpt-wrapper...

[2] https://www.youtube.com/watch?v=oFfVt3S51T4&t=1398s

Beyond the marketing value of these types of announcements, how much time until consumer grade quantum cloud computing? Years, decades?

There's some revisionism here: having the internet in your pocket anywhere you went was a clear upgrade. Projecting a screen on your palm with low resolution was a clear downgrade.

Disruption is incredibly difficult but this product was giving off Juicero vibes from the start.

Interesting they thought they could disrupt phones: devices with almost 20 years of iterative improvements, extremely mature app stores, tons of functionality, fast ubiquitous internet, etc.

You couldn't even connect the Ai Pin to your phone ?! Lock-in makes sense but it was a very risky bet.

Essential viewing: Review of the Ai Pin - The Worst Product I've Ever Reviewed... For Now (https://www.youtube.com/watch?v=TitZV6k8zfA)

This article reminds me of a tidbit about the VOC (Dutch East India Company):

"There was an extraordinarily high mortality rate among employees of the VOC due to shipwrecks, illnesses such as scurvy and dysentery, and clashes with rival trading companies and pirates. The VOC 'consumed' approximately 4,000 people per year." [1]

[1] Zanden (1993) The rise and decline of Holland's economy : merchant capitalism and the labour market

Sure you'll find folks that perhaps literally believe that AI is bigger than fire and the wheel, or whatever. Or business leaders that more cynically try to ride the hype wave with their own customers.

I think the key here is actual usage and adoption. If early adopters (marketers and coders) keep using the new tools for real work over the long term then it's a positive signal.

If you've been in SV long enough, you've seen multiple hype cycles. AI is the latest one. It doesn't mean AI is a con, there's just a tendency to exaggerate and make hyperbolic claims to sell.

AI is primarily used to write text and code. Actually integrating it into workflows across markets will take time.

A great article that is neither overly pessimistic or optimistic is Benedict Evan's The AI Summer [1]. He argues that there's a lot of excitement with big corporates but their actual adoption is low so far.

"an LLM by itself is not a product - it’s a technology that can enable a tool or a feature, and it needs to be unbundled or rebundled into new framings, UX and tools to be become useful. That takes even more time"

[1] https://www.ben-evans.com/benedictevans/2024/7/9/the-ai-summ...

Know some people who have these and apparently the AI is very limited. They were standing in front of the Golden Gate bridge and the glasses had no idea what they were looking at.

I'm sure the AI will improve quite a bit but given the hype it was a surprise.

To go big you first have to dominate a small market. Every big success started as a niche. It's not so much that you can pick the size of the success ahead of time, but rather make sure to increase the odds that things will work at all.

My advice:

1) target a large TAM - is there a large enough market of people that are willing to pay for that type of solution?

2) try to maximise problem-founder fit - what are your unfair advantages and do you have access to early adopters who can give you feedback and spread the word?

If you press people on why they believe what they believe, you will often find that the axioms underlying their reasoning are slogans, trite phrases and hackneyed soundbites.

But here's the catch: the memes, short texts, or short videos are spread through a complex machinery of interrelating parts with global reach. Explanations are plausible, wrong and very profitable in front of the right eyeballs.

They're both excellent programs. The schools have different vibes: Berkeley is much more urban and closer to SF in culture while Stanford is more of a bubble.

If you are interested in Academia after graduation, then your primary advisor is going to have a lot of influence on where you end up and the trajectory of your career. Their reputation and their network will have a lot of influence since you will be seen as a protégée of Prof X. The school tends to be a bit less important. If you're interested in industry and startups then Stanford is probably closer to that culture.

$1000-$2000+/h is not uncommon for top lawyers

What the author is missing is noblesse oblige.

Some peasants become nobles, but will never stop being peasants. Some peasants were nobles all along.

This is an interesting read. After years of conversations with folks in SV all over the socioeconomic ladder I've concluded they're 2 types of thinking:

- type 1 "employee thinking": focused on status, TC, consumption, vacation time, free time for hobbies

- type 2 "founder thinking": it's about how much value you create for other people

We (almost) all grow up and are formatted in type 1 - we look for a good "role" that brings wealth and status. The problem is when you have access to type 2 but are trapped in type 1, which seems to be the case here (the frame is about gaining money and status).

The funny thing is you can be incredibly rich, and a founder, and still think like an "employee" without ever being able to get out of it. Conversely you can be poor but think like a "founder" it's not so much about the money. In type 2, as you get richer, the scale of your impact grows and the value you can create gets bigger beyond your personal circumstances. Type 1 is not necessarily negative at all, but also can be a trap.

True but I think Spolsky meant it more as a metaphor for understanding users' psychology. Knowledge workers need empathy and creativity to solve important problems.

And design, product intuition, contextual knowledge in addition to the marketing, sales, accounting, support and infrastructure required to sell software at scale.

LLMs can help but it remains to be seen how much they can create outside of the scope of the data they were trained on.

There's a great Joel Spolsky post about developers starting businesses and realising that there's a bunch of "business stuff" that was abstracted away at big companies. [1]

One way to future proof is to look at the larger picture, the same way that coding can't be reduced to algorithm puzzles:

"Software is a conversation, between the software developer and the user. But for that conversation to happen requires a lot of work beyond the software development."

[1] The Development Abstraction Layer https://www.joelonsoftware.com/2006/04/11/the-development-ab...

Most cold emails are terrible. However when done well it can lead to interesting results. Spam/scams is different from having a real product or service in which people you reach out to might be genuinely interested. By definition it doesn’t scale all that well. If what you send is truly great then you will stand out

The need to scale is inevitable if you consider 2 trends: startups have become mainstream and the internet is orders of magnitude bigger. When YC applications consisted mostly of PG essay readers the chance of success per company was higher. Also some niche ideas can now work because of a more developed communications infrastructure, easy payments, better targeting, etc.

And knowing which companies are high quality is almost impossible at the early stages.

No code is easy to get started but difficult to customize. Code is a pain to set up but easy to modify.

It really depends how much flexibility you need: if you have to experiment, change on the fly, possibly pivot then the initial investment is usually justified with code. If your requirements are fixed and fit within the existing functionality then a no code platform might be best (for example if you’re building an app version of an existing site that’s close to templates)

Picking people is also hard, but if you narrow it down to:

1) folks who follow the directions on the application, 2) have the technical ability to build, 3) demonstrate high achievement in school/career, 4) show commitment/persistence, 5) have an idea that makes some sense, 6) are able to clearly communicate the idea, 7) have good team dynamics, 8) have some plausible strategy for growth

AND are willing to sell 7% of their startup for 125K

then the resulting pool of startups is probably smaller than you would think.

Folks had been using alternatives to rent space like HomeAway.com, VRBO.com, BedandBreakfast.com and Craigslist for years.

Airbnb won because:

- Better design, easy to use, nice pictures they took themselves at first (per PG's advice)

- Integrated payments and reviews in a seamless experience

- Popularized the idea of sharing a space when the host is there

- Offered unique accommodations in urban places

- Lots of buzz about treehouses, castles, teepees, shipping containers, etc.

- Their timing benefited from the Great Recession

- Very good at promoting their rag to riches story with YC's help

- Also you didn't need to constantly repost like Craigslist, just post once

YC's roots are definitely the software hacker/painter/kill FAANG from a coffee shop type founders, although they've shown that deep tech teams can make interesting progress without years of R&D. Finding investors that get your idea and can help with their network is paramount. YC might not be the best fit in all cases.

> YC startups don’t have to be unique. Far from it.

Slow news day. YC has made it clear over the years it's almost all about the founders not the idea. It's almost impossible to know if an idea is good at the early stages, and ideas change, startups pivot, often the timing is wrong, and the market unproven etc. More often than not most of what startups do is not unique, otherwise there's no market for it. A new take on an old idea has a much higher chance of success than something totally new that ends up being too early.

There's an interesting contradiction at the heart of Microsoft:

Its products have been the standard foundation of computing for decades, they're so ubiquitous and entrenched. Although growing up with PCs using Windows it was mediocre: slow, bloated, unintuitive, you learned to wait after a click to let it "think". Doing anything on Azure is an endless maze of "pull your hair out in frustration" astoundingly bad, everything so overly difficult. And Teams.

It's depressing that despite it all it became the standard, yet encouraging for the quality software that will one day supplant it...

The world is full of surprises, and innovation is fundamentally about replacement...aka 'disruption'

To the downvoters: you should check your definition of innovation (hint: SV angel)